Machine Learning for Lung Cancer Subtype Classification: Combining Clinical, Histopathological, and Biophysical Features
<b>Background/Objectives:</b> Despite advances in diagnostic techniques, accurate classification of lung cancer subtypes remains crucial for treatment planning. Traditional methods like genomic studies face limitations such as high cost and complexity. This study investigates whether int...
Saved in:
Main Authors: | Aiga Andrijanova, Lasma Bugovecka, Sergejs Isajevs, Donats Erts, Uldis Malinovskis, Andis Liepins |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
|
Series: | Diagnostics |
Subjects: | |
Online Access: | https://www.mdpi.com/2075-4418/15/2/127 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Cisplatin resistance alters ovarian cancer spheroid formation and impacts peritoneal invasion
by: Lydia C. Powell, et al.
Published: (2025-02-01) -
STUDY OF MAGNETOSTRICTIVE PROPERTIES OF MATERIALS BY MEANS OF METHOD OF ATOMIC FORCE MICROSCOPY
by: D. A. Stepanenko, et al.
Published: (2015-03-01) -
Detection of Human Bladder Epithelial Cancerous Cells with Atomic Force Microscopy and Machine Learning
by: Mikhail Petrov, et al.
Published: (2024-12-01) -
Molecular Subtypes of Breast Carcinoma and Their Association with Clinicopathological Features
by: Ambreen Bari, et al.
Published: (2025-01-01) -
“Subtype-precise” therapy leads diagnostic and therapeutic innovations: a new pattern for precision treatment of breast cancer
by: ZHANG Siwei, MA Ding, JIANG Yizhou, SHAO Zhimin
Published: (2024-11-01)